‘We had this problem with our database for wrinkle estimation, for example,’ he told Vice. ‘Our database had a lot more white people than, say, Indian people. Because of that, it’s possible that our algorithm was biased.’

Beauty.AI will run another contest in October and they hope to correct what appears to be bias in the system next time, as well as encourage more diversity in the entries.

Alex Zhavoronkov, chief science officer of Beauty.ai, told Vice that it is a lot easier to train machines when it comes to white faces because there are more resources focusing on them.

‘What the industry needs is a large centralized repository of high-quality annotated faces and annotated images of the various ethnic groups publically available to the public and for startups to be able to minimize racial bias,’ he said.